Literature DB >> 31136686

Characteristics of facial muscle activity during voluntary facial expressions: Imaging analysis of facial expressions based on myogenic potential data.

Eriko Kuramoto1,2, Saori Yoshinaga3, Hiroyuki Nakao1, Seiji Nemoto4, Yasushi Ishida2.   

Abstract

PURPOSE: Facial expressions are formed by the coordination of facial muscles and reflect changes in emotion. Nurses observe facial expressions as way of understanding patients. This study conducted basic research using facial myogenic potential topography to visually determine changes in the location and strength of facial muscle activity associated with voluntary facial expression to examine relationships with facial expressions.
METHODS: Participants comprised 18 healthy adults (6 men, 12 women; mean age, 24.3 ± 4.3 years). Facial myogenic potentials were measured from 19 electrodes arranged concentrically on the face, and topographic analysis was conducted. Using potential changes and topograms, the muscle activity associated with nonvoluntary facial expression and voluntary facial expressions of happiness and disgust were classified according to the characteristics of expressions. To classify homogeneous groups among the reaction of disgust, hierarchical cluster analysis was utilized.
RESULTS: One characteristic of the facial expression of happiness was activity in areas including the greater zygomatic muscle. With the facial expression of disgust, characteristic changes were seen in areas including the corrugator supercilii. Cluster analysis of the expression of disgust showed four homogeneous subgroups.
CONCLUSION: With facial myogenic potential topography, facial expressions can be evaluated objectively without being influenced by face shape or countenance. Color changes in topograms showed subtle changes in expressions that could not be supplemented with statistical processing alone, and these were useful in identifying individuality. Topography is thus expected to be utilized to supplement basic knowledge of facial expressions for a better understanding of patients.
© 2019 The Authors. Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Neuropsychopharmacology.

Entities:  

Keywords:  cluster analysis; electromyogram; facial expression; observation; topography

Mesh:

Year:  2019        PMID: 31136686     DOI: 10.1002/npr2.12059

Source DB:  PubMed          Journal:  Neuropsychopharmacol Rep        ISSN: 2574-173X


  2 in total

1.  Atlas of voluntary facial muscle activation: Visualization of surface electromyographic activities of facial muscles during mimic exercises.

Authors:  Nikolaus P Schumann; Kevin Bongers; Hans C Scholle; Orlando Guntinas-Lichius
Journal:  PLoS One       Date:  2021-07-19       Impact factor: 3.240

2.  Deep Learning-Based Pain Classifier Based on the Facial Expression in Critically Ill Patients.

Authors:  Chieh-Liang Wu; Shu-Fang Liu; Tian-Li Yu; Sou-Jen Shih; Chih-Hung Chang; Shih-Fang Yang Mao; Yueh-Se Li; Hui-Jiun Chen; Chia-Chen Chen; Wen-Cheng Chao
Journal:  Front Med (Lausanne)       Date:  2022-03-17
  2 in total

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